Senior Manager - Data Engineering at Endeavour Group

victoria, Victoria, Australia -

Full Time

Start Date

Immediate

Expiry Date

20 Jan, 27

Salary

45000.0

Posted On

22 Oct, 26

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Industry

Information Technology & Services

Description

System Delivery Enablement: Architect and maintain the "paved road" for data engineering by building self-service pipeline templates, automated CI/CD checks, and dbt testing suites that remove friction for delivery squads.
Engineering IP Guardianship: Act as the custodian of backend data assets, operationalising blueprints into reusable pipeline patterns and certifying Gold-layer models and enterprise data registries via Informatica.
People Capability Leadership: Directly guide, mentor, and develop an internal cohort of 8–10 data engineers, stepping back from day-to-day coding to foster technical mastery and team capability at scale.
Partner Vendor Governance: Embed rigorous technical acceptance criteria, runtime efficiency targets, and milestone gates into fixed-outcome Statements of Work (SOWs), holding external partners to the "Self-Onboarding Standard".
Data Reliability Standards: Establish enterprise-grade observability, data quality monitoring, and operational alerting frameworks to ensure Gold-layer datasets consistently meet downstream consumer SLAs.
Cloud Compute Efficiency: Partner with enterprise FinOps functions to implement automated cost and resource guardrails across BigQuery, cloud storage, and orchestration tooling.
Pragmatic Delivery Momentum: Champion continuous value delivery and iterative execution, making steady progress on active initiatives while systematically retiring legacy technical debt.
Modern Workflow Automation: Drive the practical adoption of Generative and Agentic AI tooling across backend engineering workflows to accelerate testing and streamline technical documentation.

Responsibilities

System Delivery Enablement: Architect and maintain the "paved road" for data engineering by building self-service pipeline templates, automated CI/CD checks, and dbt testing suites that remove friction for delivery squads.
Engineering IP Guardianship: Act as the custodian of backend data assets, operationalising blueprints into reusable pipeline patterns and certifying Gold-layer models and enterprise data registries via Informatica.
People Capability Leadership: Directly guide, mentor, and develop an internal cohort of 8–10 data engineers, stepping back from day-to-day coding to foster technical mastery and team capability at scale.
Partner Vendor Governance: Embed rigorous technical acceptance criteria, runtime efficiency targets, and milestone gates into fixed-outcome Statements of Work (SOWs), holding external partners to the "Self-Onboarding Standard".
Data Reliability Standards: Establish enterprise-grade observability, data quality monitoring, and operational alerting frameworks to ensure Gold-layer datasets consistently meet downstream consumer SLAs.
Cloud Compute Efficiency: Partner with enterprise FinOps functions to implement automated cost and resource guardrails across BigQuery, cloud storage, and orchestration tooling.
Pragmatic Delivery Momentum: Champion continuous value delivery and iterative execution, making steady progress on active initiatives while systematically retiring legacy technical debt.
Modern Workflow Automation: Drive the practical adoption of Generative and Agentic AI tooling across backend engineering workflows to accelerate testing and streamline technical documentation.